Business users have little time to perform analysis and manage every decision that must be made each day with respect to the large amounts of data being collected across various sources. Additionally, the velocity of the data being collected creates a challenge for business users to maintain a “pulse” on the health of their business. These users need to be alerted when aberrations or anomalous changes occur in their data. This often requires users to manually set up hundreds or thousands of alerts as well as select a meaningful threshold to trigger each alert and identify the aberrations or anomalous changes. Unfortunately, with increasingly large amounts of data and at the velocity the data is being collected, manually selecting a meaningful threshold for every alert is not possible.
Additionally, once these alerts are provided, users need any resulting analyses, process, and workflows to be streamlined. Although most marketing analytics software provides basic alerting functionality, these technologies fall short in intelligently focusing communication on the most relevant and important metric changes from among the flood of alerting noise. Because current technology both fails to discriminate the value and importance of different alerts and fails to apply analysis in order to combine alerts found to be similar, the recipients of the alerts and notifications experience a high degree of alert fatigue.